Oil paintings are usually considered to be two dimensional (2D) images. On closer inspection, however, oil paintings typically contain many brushstrokes, each of which is unique from the other brushstrokes. For example, each brushstroke is characterized by a unique height and color, and creates a unique texture effect according to the oil color thickness of the individual brushstroke. Therefore, oil paintings can be considered three dimensional (3D) structures having various texture effects.
The difference between the brushstrokes is in the height of the brushstrokes, which is caused from the thickness difference of the oil colors. This difference can be very small. Typically, laser scanners are used to obtain high resolution 3D data of a 3D structure having texture effects. However, even high resolution laser scanners may not provide sufficient resolution to adequately represent 3D structures of oil paintings that have very minute texture effects.
With regard to image processing, 3D oil painting reconstruction is related to artistic filters, in which various painting styles, including oil, watercolor, and line art renderings are synthesized based on either digitally filtered or scanned real-world examples. Work has been done in creating artistic styles by computer, often referred to as non-photorealistic rendering. Most of these works have been related to a specific rendering style. In various conventional image analogy techniques, a user presents two source images with the same content which are aligned, but with two different styles. Given a new input image in one of the above styles, the mapping from an input image to an aligned image of the same scene in a different style is estimated. The aligned image pair with the same scene but in a different image style, however, is often unavailable.
In another conventional technique, for a given input image, only one source image of an unrelated scene that contains the appropriate style is required. In this case, the unknown mapping between the images is inferred by Bayesian technique based on belief propagation and expectation maximization. These conventional techniques, however, have been typically limited to 2-dimensional image construction in which only limited types of texture effects were reconstructed.